Collagen-Derived Cryptides: Machine-Learning Prediction and Molecular Dynamic Interaction Against Klebsiella pneumoniae Biofilm Synthesis Precursor


  • Ahmad Al-Khdhairawi Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Siti Mariani Mhd-Marzuki Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Zi-Shen Tan Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Narin Shan Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Danish Sanuri Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Rahmad Akbar Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
  • Su Datt Lam Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
  • Fareed Sairi Department of Biological Science and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia


Collagen, antibiofilm peptide (AMP), Klebsiella pneumoniae, molecular docking, MrkH, Type 3 fimbriae


Collagen-derived cryptic peptides (cryptides) are biologically active peptides derived from the proteolytic digestion of collagen protein. These cryptides possess a multitude of activities, including antihypertensive, antiproliferative, and antibacterial. The latter, however, has not been extensively studied. The cryptides are mainly obtained from the protein hydrolysate, followed by characterizations to elucidate the function, limiting the number of cryptides investigated within a short period. The recent threat of antimicrobial resistance microorganisms (AMR) to global health requires the rapid development of new therapeutic drugs. The current study aims to predict antimicrobial peptides (AMP) from collagen-derived cryptides, followed by elucidating their potential to inhibit biofilm-related precursors in Klebsiella pneumoniae using in silico approach. Therefore, cryptides derived from collagen amino acid sequences of various types and species were subjected to online machine-learning platforms (i.e., CAMPr3, DBAASP, dPABBs, Hemopred, and ToxinPred). The peptide-protein interaction was elucidated using molecular docking, molecular dynamics, and MM-PBSA analysis against MrkH, a K. pneumoniae’s transcriptional regulator of type 3 fimbriae that promote biofilm formation. As a result, six potential antibiofilm inhibitory cryptides were screened and docked against MrkH. All six peptides bind stronger than the MrkH ligand (c-di-GMP; C2E).


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How to Cite

Al-Khdhairawi, A., Mhd-Marzuki , S. M., Tan, Z.-S., Shan, N., Sanuri, D., Akbar, R., Lam, S. D., & Sairi, F. (2022). Collagen-Derived Cryptides: Machine-Learning Prediction and Molecular Dynamic Interaction Against Klebsiella pneumoniae Biofilm Synthesis Precursor. Malaysian Applied Biology, 51(5), 59–75.